Panoply is a smart data warehouse that automates all three key aspects of the data analytics stack: data collection & transformation (ETL), database storage management, and query performance optimization. Panoply empowers anyone working with data analytics to quickly gain actionable insights on their own - without the need of IT and Engineering.
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Website | panoply.io |
Pricing URL | Official Panoply Pricing |
Details $ | paid Free Trial $200.0 / Monthly |
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Website | aws.amazon.com |
Pricing URL | - |
Details $ | - |
Based on our record, Amazon EMR should be more popular than Panoply. It has been mentiond 10 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
The service I used was Panoply. https://panoply.io/. Source: almost 2 years ago
Instead of building everything from scratch, you can try https://panoply.io/. Source: almost 2 years ago
Thanks will check this out. Currently we are testing with https://panoply.io/ but it's expensive. Source: over 2 years ago
There are different ways to implement parallel dataflows, such as using parallel data processing frameworks like Apache Hadoop, Apache Spark, and Apache Flink, or using cloud-based services like Amazon EMR and Google Cloud Dataflow. It is also possible to use parallel dataflow frameworks to handle big data and distributed computing, like Apache Nifi and Apache Kafka. Source: about 1 year ago
I'm going to guess you want something like EMR. Which can take large data sets segment it across multiple executors and coalesce the data back into a final dataset. Source: almost 2 years ago
This is exactly the kind of workload EMR was made for, you can even run it serverless nowadays. Athena might be a viable option as well. Source: almost 2 years ago
Apache Spark is one of the most actively developed open-source projects in big data. The following code examples require that you have Spark set up and can execute Python code using the PySpark library. The examples also require that you have your data in Amazon S3 (Simple Storage Service). All this is set up on AWS EMR (Elastic MapReduce). - Source: dev.to / over 2 years ago
Check out https://aws.amazon.com/emr/. Source: almost 2 years ago
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